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NOAA AVHRR image referencingDIEM HO a & ADEL ASEM aa IBM Scientific Center, 36 Ave, Raymond Poincare, Paris, 75116, FranceVersion of record first published: 27 Apr 2007.

To cite this article: DIEM HO & ADEL ASEM (1986): NOAA AVHRR image referencing, International Journal of Remote Sensing,7:7, 895-904

To link to this article: http://dx.doi.org/10.1080/01431168608948898

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INT. J. REMOTE SENSING, 1986, VOL. 7, No.7, 895-904

NOAA AVHRR image referencing

DIEM HO and ADEL ASEM

IBM Scientific Center, 36 Ave. Raymond Poincare, Paris 75116. France

(Received 27 November /985; in final forrn 2/ January /986)

Abstract. A simple and fast algorithm for image referencing of the NOAA(National Oceanic and Atmospheric Administration) AVHRR (Advanced VcryHigh Resolution Radiometer) data has been derived to facilitate the identificationof geographic co-ordinates corresponding to any pixelon an NOAA image and viceversa. The procedure assumes a spherical Earth and circular orbit and takes intoaccount the effects due to the Earth's rotation and oblateness and the scan skew.Inputs to the procedure are the ascending nodal longitude and time, the time of thefirst scan lineand one ground control point (GCP). The effectsof an ellipsoid Earthand an elliptical orbit are corrected by using the GCP to adjust the spacecraftaltitude and inclination angle. No detailed emphemcris data are required. Theaverage r.m.s. errors obtained by comparing with independent sets of well­distributed GCPs for each image are about 2pixels and 2 lines or 3 km displace­ment. Results from the procedure are illustrated by the rectification of NOAAimages over France.

1. IntroductionImages acquired by remote sensing are subjected to different distortions due to the

Earth's curvature and rotation, the spacecraft's speed, altitude and attitude, the scanskew and the projection of a spherical surface on a flat image. These distortions, if notproperly accounted for, will prevent meaningful comparison among images, partic­ularly in sequential image analysis or multisatellite data studies. Therefore, the needfor image referencing, i.e. identifying the geographic co-ordinates corresponding to animage pixel (picture element) or locating a pixel corresponding to given geographic co­ordinates, is inevitable in many satellite data studies.

Extensive work has been done on the geometric correction of LANDSAT data. Thecorrection requires a model that does image referencing to transformlatitude/longitude co-ordinates to image co-ordinates. For example, Bernstein (1976,1983) used at least 16 GCPs to fit a polynomial which was then used to interpolate therest of the image. Orti (1981) used an optimal distribution of reference points tosimulate the attitude and altitude of the satellite. Sawada et al. (1981) described ananalytic model which required the attitude information on the SlAT (scene imageannotation tape) and three GCPs to correct the geometric distortion. Friedmann et al.(\ 983) used a complex attitude model to rectify ten consecutive LANDSAT scenesusing as few as four GCPs. Forrest (1981) used the geographic co-ordinates at theimage centre and the attitude information at this point to develop a correction modelfor day-time images. However, in many images, the centre point may not beidentifiable and the attitude information at that point may not be available. Most ofthese techniques claim to achieve errors within I or 2 pixels, where the errors areusually calculated by comparing the GCPs with the values given by the polynomialswhich fit through them. Some of these models require the satellite orbit and attitude

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. information which might not be reliable (Sawada et al. 1981). Others require largenumber of well-defined and well-distributed GCPs. The process of locating manyGCPs is often tedious, time consuming and sometimes even impossible (Friedmann etal. 1983).

NOAA AVHRR data are widely used in weather, climate and environmentalstudies due to their high spatial and radiometric resolution and accurate onboardcalibration system. Nevertheless, there are few published articles on the imagereferencing or geometric correction of AVH RR data. Procedures for LAN DSAT thatrequired precise attitude information cannot be modified to apply to NOAA satellite,because-the tracking data may not be accurate (Clark and LaViolette 1981). Otherprocedures using a large number ofGCPs can be applied, but the problem of finding alarge and well-distributed set of GCPs in AVHRR images is even more difficult thanthe LANDSAT. LANDSAT observes land areas with typically fixed features whereasmany AVHRR scenes of interest are of ocean or polar regions with few identifiablecontrol points.

With these constraints for NOAA imageries, Legeckis and Pritchard (1976)proposed a simple algorithm for correcting only the geometric distortions due to theEarth curvature, Earth rotation and spacecraft roll. Other effects were ignored. In theirprocedure, for the Earth rotation correction, the altitude was assumed constant for thewhole scene (about 1000 km). The satellite roll correction assumed a spherical Earth,but the asymmetry due to the Earth's oblateness and the satellite orbit was not takeninto account. Their average error, representing the misalignment over a distance of1000 km, is ten samples, or 5 krn, for NOAA-4 data. Recently, Clark and LaViolette(1981) have tested the accuracy of the geographic co-ordinates provided by NOAANESS (National Environmental Satellite Service) at 51 equally spaced intervals alongeach scan line ofTIROS-N data; they found that the positioning errors are from 2 to4 pixels. The geographic grids provided with the AVH R R data from the CM S-Lannion(Centre Meteorologic Spatiale at Lannion, France) have errors of the order of 5 km.Emery and Ikeda (1984), using high-quality U.S. Navy emphemeris data for NOAAsatellites and seven GCPs, were able to rectify the AVHRR images to 1·5 km errors.

Our objective is to derive a simple and accurate procedure not only to compute thegeographic co-ordinates for a given pixel but also to locate the pixel on an image forgiven geographic co-ordinates, hence image referencing. The procedure should use aminimum number ofGCPs (one GCP as described in our model) and easily accessiblesatellite ancillary data. That excludes the possibility of having a dynamic orbital andattitude model due to the inaccessibility of high-quality orbit and attitude information.

Our model assumes a spherical Earth and circular orbit and takes into account therotation and oblateness of the earth as those of Duck and King (1983). We alsoconsider the effect due to the scan skew and use one GCP to adjust the satellite altitudeand inclination angle for each image. The procedure was successfully tested withNOAA AVH RR data. We shall present an analysis and description of the procedure,together with the results of ten test cases, nine of which were selected and provided bythe CNES (Centre National d'Etudes Spatiales, Toulouse, France) for this purposeand the other was obtained from the CMS-Lannion. Application of the procedure tothe rectification of NOAA images covering France is also illustrated.

2. ModelThis section describes the technique developed for image referencing. First are

listed the three models for the orbit, the scanner and the Earth. These are followed by

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the three procedures for (i) direct referencing (computing latitude/longitude for givenline/pixel), (ii) inverse referencing (compouting line/pixel for given latitude/longitude),and (iii) determination of the satellite altitude and inclination angle using one GCP.Normally the third procedure would be applied to compute the satellite altitude andinclination angle and these values are subsequently used in the direct and inversereferencing procedures.

The configuration for referencing a geographic area viewed by the NOAA satelliteis illustrated in figure 1. The symbols are defined in the Appendix. Constants,parameters and empirical relations or nominal values are similar to those described byDuck and King (1983) and the NOAA Technical Memorandum (NOAA 1978).

2.1. Analysis2.1.1. The Orbit

The angular speed is defined by the free-fall speed at which the centripetalacceleration equals the gravitational acceleration.

() = J(Il/r3) (I)

,-: .: 0, "'10"

I..-.....~

Figure I. The satellite-static Earth configuration.

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898

where

D. Ho and A. Asem

r=Re+h, (2)

Thus the angular span from the ascending node to the subsatellite point is:

l:J=t[J(Jllr3) ] (3)

2.1.2. The scannerThe off-nadir viewing angle is defined by

lJ = pDi (4)

and D is defined as negative to the left of the nadir trace looking in the satellite flightdirection and positive otherwise. For the NOAA-7 AVHRR system, Di=0'955

x 1O- 3 rad .There is also a relationship between the satellite zenith angle and the off-nadir

viewing angle (see triangle SOD' on figure I).

z = arc sin [(rlRe) sin D]= if! +D (5)

where if! is negative to the left of the nadir trace looking in the satellite flight directionand positive otherwise.

2.1.3. The EarthThe Earth's angular velocity relative to the orbit plane is contributed by the Earth's

inertial rate and the inertial precession rate (Duck and King 1983)

A.=2nID,-n (6)

The precession, caused primarily by the Earth's oblateness, is represented by n, therate of change of the longitude.

The scan skew effect is accounted for by the satellite azimuth angle, )I, which iscomputed from the scan line and the nadir trace by

)I=arccos(Ot,/zlifimax) (7)

The contribution of this effect is quite small, and for NOAA-7 this y is only slightly off90°.

For a static spherical Earth, from figure I we can deduce four principaltrigonometric equations:

cos {3 =cos if! cos I:J +sin if! sin I:J COS)l

. . .) sin if! sin)lsm(l-J = . {3

sm

(8)

(9)

(II)

(10)sin <PD' = sin {3 sin)

cos {3cos AD' =--­

COS<PD'

Note that <PD' and )'D' are the latitude and longitudinal displacement from ascendingnode of the viewpoint in a non-rotating Earth model.

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NOAA AVHRR image referencing 899

2.2. Procedures2.2.1. Direct referencing

From a given pixel defined by a pair of line and pixel numbers (I, p), the procedureallows us to locate its corresponding geographic co-ordinates. This is done by:

(I) Calculate I as I=(I-I)/(Iine rate)+lr-lnod '

(2) Calculate efrom I by equation (3).(3) Given p, calculate (j and t/J by equations (4) and (5).(4) Determine f3 andj by equations (8) and (9), successively.(5) Calculate t/>D' and A.D' by equations (10) and (II), respectively.

Note that line rate is the number oflines scanned per second. During the time I, theEarth has rotated. This rotation only affects the longitude but not the latitude. Thegeographic co-ordinates corresponding to the given (I,p) are:

(12)

and

(13)

Assuming that the eastward movement of the Earth is in the positive direction, therotational effect has to be subtracted from the longitude. This is different from a similarexpression given by Duck and King (1983).

2.2.2. Inverse referencingGiven a set of geographic co-ordinates, this procedure allows us to identify the

corresponding image co-ordinates (I,p) on an AVHRR image. This process is morecomplicated than direct referencing because the time I from the ascending node to thescan line of the pixel is not known and must be calculated by iterations. Initially, weassume l=/f-tnod ,

(I) From I, calculate )'D' by equation (13).(2) From A.D' and t/>D or t/>D" calculate f3 by equation (II).(3) Calculate j, t/J and eby equations (10), (9), and (8), successively.(4) Calculte the new time I' by equation (3).(5) [f(~I=It'-II":;BI) then go to (6); else 1=1+0·581, go to (I) (B 1 =0'001).(6) Calculate (j from t/J by equation (5).(7) Calculate pixel number, p, from (j by equation (4).(8) Calculate line number, I, as 1= (I-Ir) x line rate + I.

2.2.3. Determination of satellite altitude and inclination angleAssuming that we have a GCP of known longitude and latitude at image co-

ordinates (I, p), the procedure consists of:

(I) Calculate (j and I from given (I, p).(2) Assign i = inominaJ' h, = hnominal'

(3) Calculate 0 and}' from equations (I) and (7), respectively.(4) Calculate An' then A.D' by equations (6) and (13).(5) Calculate p,j, t/J and eby equations (II), (10), (9), and (8), successively.(6) Calculate /1 1 from (j and t/J by equation (5).(7) Calculate /1 2 from eby equation (3).

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900 D. Ho and A. Asem

(8) Calculate I/J and i from h2 by equations (5) and (9), successively.(9) Set h, =h2 •

(10) If(lh1-h21:S;:6 2) then exit; else go to (3) (62=500,00).

3. Results and applicationsA set of ten NOAA AVHRR images of both ascending and descending paths was

tested (see the table). The first image, obtained from the CMS-Lannion, was on adescending path. The other nine, selected and provided by the CNES-Toulouse for thispurpose, were on their ascending paths. On each image, from 10 to 25 GCPs, whosegeographic co-ordinates were scaled from the Time Atlas of the World and theMediterranean Sea Map (scale I: I 250000) of the Institut Geographic National(France), were located for their line and pixel numbers (l,p). At first, we applied thenominal values of the satellite altitude and inclination angle to the two first procedures,the results yielded r.m.s. errors of 57 lines and 8 pixels and 0.5 0 latitude and 0.35 0

longitude for the first image. We believe the errors are primarily due to the assumptionsof nominal values for the satellite attitude and the orbit inclination angle in thespherical Earth and circular orbit models. To reduce these errors, we have used thethird procedure with one randomly selected GCP to adjust the satellite altitude andinclination angle for each image. The newly found altitude and inclination angle arethen used as inputs for the direct and inverse referencing procedures described above.Note that the nodal longitude and the ascending time were extracted from the headerof each image on the CCTs (computer compatible tape). The whole procedure isillustrated in figure 2. The rest of the GCPs are used for the calculation of the real r.m.s.error for each image. The results are shown in the table.

The mean Lm.S. errors for line and pixel are 1·76 and 2,30, respectively, for inversereferencing. The average geographic displacement is 3·15 km corresponding to thedirect referencing. The errors in displacements are calculated from the geographicshifts of the GCPs. It should be noted that these Lm.S. errors are different from thoseoften discussed in other geometric correction procedures, whose r.m.s. errors are

Resultsof NOAA AVHRR image referencing for ten test cases. The Lm.S. errors are calculatedwith the GCPs sealedon maps and images.Errors in lineand pixelcorrespond to inversereferencing, and errors indistance calculated from the displacementof the geographicco­ordinates correspond to direct referencing.

Root mean square error

No. Date Orbit Line Pixel Distance (km)

I 3 November 1982 7025 (·98 2·64 3-912 18 February 1983 8543 1·89 3·22 3·453 3 March 1983 8726 1·26 2·19 3·514 8 March 1983 8797 2·45 2-43 2-455 15 April 1983 9334 2·09 (·73 3·176 14 July 1983 10605 2·32 2·45 3-677 21 July 1983 10704 1·90 2·17 3-828 4 December 1983 12624 1·09 2·17 2·33'9 5 December 1983 12638 0·95 1·21 1·8510 27 April 1984 14672 1·64 2·75 3·25

AverageLm.S. error ',76 2·30 3·15

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NOAA AVHRR image referencing 901

coordinates of thoref.rence point(line,pl .el,lal. ,long.)

"...".. Ior Ulatitude,longltude!

satellite ancillaryand nominol orbitparameters

......__.. .. --_._--_...

calculation of scanner modelaltitude and altitude orbit model latitude. longitudeinclination inclination angle

~

Earth model orangle IIne,pheel

I' i

.._-------- ._-----------

Figure2. The schematic procedurefor satellite image referencing.

usually calculated from the same GCPs used to generate the mapping polynomial.They do not represent the real errors seen on the image.

In all ten cases, the inclination angle varies from 98·887 to 99,081°, compared withits nominal value of 98·899°. The altitude varies from 820 to 853 km well within thenominal range of NOAA-7.

Figure 3 illustrates an example ofour referencing procedure, two NOAA images arerectifiedand mapped onto a geographic grid. The near-infrared image (band 2) oforbitnumber 8797 on 8 March 1983is displayed in green. The second image is also of band 2of orbit number 9334 on 15 April 1983 displayed in red. Each line represents one­hundredth of a degree, and each pixel is one-sixtieth ofa degree. This grid size has beenused in order to fit the whole of France within an image of 1024 pixels x 1024 pixels.The task consists of calculating the satellite altitude and inclination angle for eachimage and then using inverse referencing to identify the image co-ordinates corres­ponding to the predetermined geographic co-ordinates. A resampling routine isapplied to rectify the two images onto the grid. This example also shows a potentialapplication of the procedure for cartographic mapping. Map accuracy can be verifiedwith the labelled grid. In addition, we have used two superimposed images to check therelative errors between them by comparing the resultant image. Virtually no shiftingcan be detected on the Mediterranean Sea. Lake Geneva, for example, on the rightcentre of the image is very well defined. The precision can be seen by the finedefinitionof the rivers on the map. There is some shifting of up to 5 pixels on the Atlantic coastbetween the two images. Note that the shifting shown here is larger than the averager.m.s. errors given in the table because they are the relative errors between the twoimages. The outstanding red and green patches and spots on the image are clouds. Thecut on top of the figure is due to the deformations and different coverage of the twoimages.

Application of this procedure to the registration of NOAA images withMETEOSAT images has also been done successfully over Italy and Yugoslavia (see,for example, Ho and Asem 1984a, 1985). Rectified NOAA temperature imagescovering Tunisia have also been used to calibrate METEOSAT data (Ho 1985). The

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902 D. Ho and A. Asem

Figure 3. NOAA image rectification. Two near-infrared images covering France on 8 March1983 (green) and on 15April 1983 (red) are mapped onto a geographic grid to illustratethe accuracy or the image referencing procedure (see also the text).

procedure is currently used to extract satellite radiometric temperatures correspondingto the sea surface temperatures measured in situ by ships and to help in temporal studyusing non-registered AVHRR images.

4. Concluding remarksThe above results suggest that this procedure can be used in many remote-sensing

applications, such as geometric correction, registration, temporal analysis, sea surfacetemperature studies and multisatellite data correlation and calibration. The procedurecan be fully automated by using a search algorithm to identify the necessary GCP in theproximity of the pixel located by the inverse procedure using nominal values (see, forexample, Ho and Asem 1984 b). The procedure is simple and requires little executiontime and effort. No actual satellite orbital or attitude data are required. The results arecompared more favourably with those provided by NOAA (see, for example, Clarkand LaViolette 1981). As shown above, our procedure requires precise nodal

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NOAA AVHRR image referencing 903

information, which is currently available on the CMS-Lannion data but not on theNOAA SDSD image tapes. It would be of great service to users if NOAA wouldincorporate this nodal information on its CCTs. The accuracy of the procedure alsodepends on the precision of the nodal information, particularly for images ofascendingpaths. [f the nodal time and longitude are not reliable, a second GCP may be used toadjust them.

The altitude and the inclination angle obtained by this procedure may not be theactual instantaneous altitude and inclination angle of the satellite at that moment, dueto the complexity of all satellite parameters involved. However, the resulting values ofthe altitude and inclination angle are so close to the nominal values that they can beconsidered as the effective values for that image. In fact, adjustment of the satellitealtitude and inclination angle in our procedure has the effect of zooming, translatingand rotating. Thus, it implicitly takes into account some effects due to the satelliteattitude.

In cases where many GCPs are identifiable on an image, a static model of satelliteattitude can be assumed to adjust the system bias in lines and pixels (Emery and Ideda1984). However, in our experience, this step may not be necessary because the averageerrors in lines and pixels are so small that the possible adjustment is virtually negligible.

AcknowledgmentsThe authors would like to thank Y. Kerr ofCNES for providing the NOAA testing

data and W. Nikblack for critically reading the manuscript. This work has been donewithin the scope of the TBMjCNRSjCNES Climatology Project.

AppendixNotationD, = 86 164·09s, the sidereal dayh, Orbital altitude (nominally at 833 km)i Inclination angle (degrees)j Angle formed by the arc (pixel to node) and the quatorial plane (rad)J 2 = 0·00 I08263, Earth oblateness coefficientp Number of pixels counting from ssp - 0·5 (ssp: subsatellite point)R, Radius of Earth (= 6 378 160m)I Time from the ascending node to the scan line of interest (s)11/ 2 Half scan line time (s)If Time of first scan line (s)I nod Nodal time (s)z Zenith angle (rad)P Angle spanned from ascending node to the pixel (rad)y Satellite azimuth angle relative to the orbit plane (rad)o Off-nadir viewing angle (rad)0i Scan step angle (rad)f} The Earth angle from the ascending node to the ssp (rad)o Angular speed (rad)AD The Earth longitude (degrees))'0' Static Earth longitude (rad))'nod Nodal longitude (degrees)An Earth angular velocity (radjs)J1 Earth gravitational constant (=3,98603 x 1014m3s- 2)

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904 NOAA AVHRR image referencing

tPD The Earth latitude (degrees)tPD' Static Earth latitude (rad)'" Arc defined by the viewing pixel and the ssp (rad)"'max Earth angular span of half scan line (rad)n= -1'5J2R:Jw-3'5cosi(rad/s)

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